Abstract
Typical medical image annotation systems use manual annotation or complex proprietary software such as computer-assisted-diagnosis. A more objective approach is required to achieve generalised Content Based Image Retrieval (CBIR) functionality. The Automated Medical Image Collection Annotation (AMICA) toolkit described here addresses this need. A range of content analysis functions are provided to tag images and image regions. The user uploads a DICOM file to an online portal and the software finds and displays images that have similar characteristics. AMICA has been developed to run in the Microsoft cloud environment using the Windows Azure platform, to cater for the storage requirements of typical large medical image databases.
| Original language | English |
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| Title of host publication | The Fourth International Conference on Advances in Databases, Knowledge, and Data Applications : DBKDA 2012 : February 29 - March 5, 2012, Saint Gilles, Reunion Island |
| Publisher | Curran Associates |
| Pages | 182-186 |
| Number of pages | 5 |
| ISBN (Print) | 9781612081854 |
| Publication status | Published - 2012 |
| Event | International Conference on Advances in Databases_Knowledge_and Data Applications - Duration: 29 Feb 2012 → … |
Conference
| Conference | International Conference on Advances in Databases_Knowledge_and Data Applications |
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| Period | 29/02/12 → … |
Keywords
- cloud computing
- diagnostic imaging
- content-based image retrieval
- image repositories
- image analysis